build_base_ensemble: Wrapper for creating an ensemble

In tsensembler: Dynamic Ensembles for Time Series Forecasting

Description

Using the parameter specifications from model_specs-class, this function trains a set of regression models.

Usage

build_base_ensemble(form, data, specs, num_cores = 1)

Arguments

form	formula;
data	data.frame for training the predictive models;
specs	object of class model_specs-class. Contains the information about the parameter setting of the models to train.
num_cores	number of cores

Value

An S4 class with the following slots: base_models, a list containing the trained models; pre_weights, a numeric vector describing the weights of the base models according to their performance in the training data; and colnames, the column names of the data, used for reference.

Examples

data("water_consumption")
dataset <- embed_timeseries(water_consumption, 5)
specs <- model_specs(c("bm_ppr","bm_svr"), NULL)
M <- build_base_ensemble(target ~., dataset, specs, 1)

tsensembler documentation built on Oct. 27, 2020, 5:07 p.m.